The present invention relates to object detection in medical images, and more particularly, to multiple object detection using sequential Monte Carlo and a hierarchical detection network.
Multiple Object Detection has many applications in computer vision systems, for example in visual tracking, to initialize segmentation, or in medical imaging. For example, in medical imaging, multiple anatomic objects having a spatial relationship with each other can be detected. State of the art approaches for multi-object detection typically rely on an individual detector for each object class followed by post-processing to prune spurious detections within and between classes. Detecting multiple objects jointly rather than individually has the advantage that the spatial relationships between the objects can be exploited. However, obtaining a joint model of multiple objects is difficult in most practical situations.